Grounded in real-world use cases, this book moves from fundamentals to boardroom-ready execution. You’ll start with the core concepts behind AI, machine learning, and GenAI, then pivot into the challenges of FSS: intense regulatory scrutiny, evolving fraud threats, operational complexity, and rising expectations for personalized, always-on service. You’ll learn a practical blueprint for GenAI adoption, including strategy, governance, risk controls, data readiness, and culture—through the lens of executives tasked with delivering measurable value responsibly.
From there, you’ll get hands-on experience building GenAI systems: prompt design, evaluation, Retrieval-Augmented Generation (RAG), fine-tuning, and agentic workflows. You’ll see how these capabilities power mission-critical functions across the enterprise: Finally, you’ll operationalize all of it with modern FMOps/LLMOps practices—security, privacy, performance, cost management, monitoring, and continuous improvement—so pilots become production systems that scale. The closing chapter distills emerging trends, from autonomous agents to domain-specialized models, and lays out next steps so your organization can adopt GenAI with confidence, compliance, and a clear return on investment.
Whether you’re a CIO crafting a roadmap, a product leader shipping AI features, a data scientist building RAG pipelines, or a risk and compliance executive seeking control and clarity, this book is your end-to-end guide to deploying GenAI that is safe, explainable, and enterprise-grade.
What You Will Learn
• Develop a strategic blueprint for GenAI adoption, including implementation methodologies, risk mitigation, and best practices for financial institutions
• Master the core components of building GenAI applications, from prompt engineering and model evaluation to RAG and Agentic AI
• Discover how GenAI transforms risk and compliance management, including applications in Anti-Money Laundering (AML), trade surveillance, and regulatory reporting
• Explore practical GenAI use cases across retail banking, investment banking, and wealth management, and learn about successful operational deployment
Who This Book Is For
Data scientists, AI professionals, and financial services experts interested in leveraging generative AI within the financial sector.
Grounded in real-world use cases, this book moves from fundamentals to boardroom-ready execution. You’ll start with the core concepts behind AI, machine learning, and GenAI, then pivot into the challenges of FSS: intense regulatory scrutiny, evolving fraud threats, operational complexity, and rising expectations for personalized, always-on service. You’ll learn a practical blueprint for GenAI adoption, including strategy, governance, risk controls, data readiness, and culture—through the lens of executives tasked with delivering measurable value responsibly.
From there, you’ll get hands-on experience building GenAI systems: prompt design, evaluation, Retrieval-Augmented Generation (RAG), fine-tuning, and agentic workflows. You’ll see how these capabilities power mission-critical functions across the enterprise: Finally, you’ll operationalize all of it with modern FMOps/LLMOps practices—security, privacy, performance, cost management, monitoring, and continuous improvement—so pilots become production systems that scale. The closing chapter distills emerging trends, from autonomous agents to domain-specialized models, and lays out next steps so your organization can adopt GenAI with confidence, compliance, and a clear return on investment.
Whether you’re a CIO crafting a roadmap, a product leader shipping AI features, a data scientist building RAG pipelines, or a risk and compliance executive seeking control and clarity, this book is your end-to-end guide to deploying GenAI that is safe, explainable, and enterprise-grade.
What You Will Learn
• Develop a strategic blueprint for GenAI adoption, including implementation methodologies, risk mitigation, and best practices for financial institutions
• Master the core components of building GenAI applications, from prompt engineering and model evaluation to RAG and Agentic AI
• Discover how GenAI transforms risk and compliance management, including applications in Anti-Money Laundering (AML), trade surveillance, and regulatory reporting
• Explore practical GenAI use cases across retail banking, investment banking, and wealth management, and learn about successful operational deployment
Who This Book Is For
Data scientists, AI professionals, and financial services experts interested in leveraging generative AI within the financial sector.
Transforming Financial Services with Generative AI: From Strategy and Design to Practical Applications
175
Transforming Financial Services with Generative AI: From Strategy and Design to Practical Applications
175Paperback(First Edition)
